this is based on calsyslab project
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  1. import pickle
  2. from MarketPlaces.Classifier.transformer import load
  3. title_transformer_file = r"..\Classifier\product_title_transformer.pickle.new"
  4. content_transformer_file = r"..\Classifier\product_content_transformer.pickle.new"
  5. classifier_file = r"..\Classifier\marketplace_lr.pickle"
  6. with open(classifier_file, 'rb') as f:
  7. clf = pickle.load(f)
  8. title_transformer = load(title_transformer_file)
  9. print(title_transformer.ngram_list)
  10. content_transformer = load(content_transformer_file)
  11. print(content_transformer.ngram_list)
  12. X_1 = title_transformer.transform("Anubis banking botnet v8.0")
  13. X_2 = content_transformer.transform("Anubis 8.0 Android Banking BotNet is a Advance builder modernized and updated. Apk (build) + admin file Download https://anonfiles.com/Naa9M1Ubx9/159_zipPsw CarlosDonCC2022")
  14. print(X_1)
  15. print(X_2)
  16. X = [X_1 + X_2]
  17. result = clf.predict_proba(X)[0]
  18. print(result)